One of the common ways for detecting heart rates used by many existing sports equipment requires a user to hold onto metal heartbeat sensing grips provided on the sports equipment before heart rates can be measured. The shortcomings of this process include poor comfort, risk of electric shock, and hygiene concerns. Therefore, a non-contact detection method is suggested for determining heart rate activity, for example, through image recognition to determine the heart rate activity of a user.
However, there are many technical problems associated with capturing images and performing image recognition and processing while a user is using a sports equipment. In particular, when the user/subject is in motion, the camera on the sports equipment may also be in motion, e.g., shaking. In this circumstance, there is a relative movement between the camera and the subject, and an image thus captured is called a dynamic image, which is different from a static image in which there is no relative movement between the camera and the subject. Image processing for dynamic images is generally significantly more complex than the image processing for static images. For example, dynamic images will have problems such as image blurs, tracking of a region of interest (ROI), and light source correction. Image blurs are usually caused by shaking of the camera and/or the subject. When an ROI is selected and being tracked, light distributions of continuous frames of the ROI may vary due to the relative movements. For example, when a user is moving vigorously, if the facial area of the user is fixed, which is equivalent to a vigorously moving environment, there will be uneven ambient light distribution. This will result in errors in image analysis. Therefore, in order to use dynamic image analysis for determining heart rate activity of the user, the problem associated with light instability must be resolved.
If a heart rate activity detection based on dynamic images is performed using a heart rate activity detection technique based on static images, peak offsets may occur, which lead to calculation errors of the heart rates. If the heart rate detection technique based on static images is used and adjusted using a RGB color space, there will be two problems. The first problem is that, under a fixed light source, R, G, B coefficients for creating color channels of this ambient condition are constant. However, due to the relative motions between the camera and the subject, light conditions will not be the same, and, therefore, the heart rate detection technique based on static images cannot be applied to dynamic images. The second problem is that, if a RGB color space is used for image correction, the brightness and the saturation will also be changed. In this case, the saturation component of each of the original RGB color channels will also be changed, thereby affecting the reliability of using the RGB color space for heart rate detection.